Far too many people in the data management industry think that there is a one-size-fits-all, static solution that will solve all data-related problems – and they spend a lot of their time promoting this idea. In reality there’s no such thing. This tired old fallacy has been hauled out for far too long, and unfortunately there are too many organizations that are just beginning to realize that what they’ve bought isn’t a solution – it’s just another problem.

So let’s go back to basics. Any data management infrastructure has to be appropriate for the size of the firm and the type of operation. The solution that is right for a 40-person hedge fund is very different from the solution needed by a global custodian with thousands of customers and tens of thousands of employees.

Most firms have multiple business units, product lines, and investment strategies – all of which require different data sets used in different ways. Accounting and risk management will need different data sets than the trading desk. Operations want data on actual holdings, so analysts can use it for modeling ‘what if’ scenarios. The idea that you can impose a monolithic, inflexible data management structure with a single data set and a single management tool, onto the modern business with all its complexities is manifestly false.

So let’s have a more realistic conversation about data management. And let’s start by calling out old-fashioned ideas about data management, and exposing them for the myths that they really are.